The present invention relates to Fourier Transfer Infrared (FTIR) spectrophotometer, more specifically, to devices capable of reducing the baseline noise of FTIR spectrophotometer. The present invention relates to U.S. Published Patent Application 20070291255, Ser. No. 11/845,580, filed Aug. 27, 2007, the disclosure of which is incorporated herein by reference in its entirety.
A fundamental property of a sample, be it gas, liquid or solid, is its tendency (or lack of tendency) to affect light at certain wavelengths. Characterization of the tendency of a sample to absorb, scatter, or transmit light is the basis for spectrophotometry. Exemplary applications of spectrophotometry include chemical and biological sample analysis. Other exemplary applications include manufactured product testing and the testing of air or water quality.
One significant aspect of any application of quantitative spectrophotometry is the ability to numerically characterize a sample. Thus, quantitative spectrophotometry reveals sample properties and allows one sample to be differentiated from another. In particular, aspects of spectrophotometry are often applied to determine optical spectra for samples in order to generally characterize and distinguish the samples. For example, aspects of spectrophotometry may be used to determine an absorption spectrum and/or a transmittance spectrum of a sample for identifying the sample or differentiating it from another sample. A sample's absorption spectrum indicates the fraction of light absorbed by the sample for a particular range of wavelengths. A sample's transmittance spectrum indicates the faction of light which passes through the sample for a particular range of wavelengths. The range of wavelengths may include one or more of the following ranges of light: ultraviolet (UV), visible, and infrared (IR).
Two general methods by which optical spectra, such as absorption and transmittance spectra, are obtained are (i) dispersive scanning (hereinafter referred to as “DS”) and (ii) Fourier Transform (hereinafter referred to as “FT”). Both methods include facilitating an interaction between a sample light beam and a sample and detecting light (e.g., transmitted light, reflected light, scattered light) resulting from the interaction. Similarly, both methods include facilitating an interaction between a light beam and a reference or a sample, and detecting light (e.g., transmitted light, reflected light, scattered light) resulting from the interaction. For both methods, an optical spectrum is obtained from the ratio of the detected light for the sample to the detected light for the reference. According to the DS method, the sample light beam and the reference light beam each contain light having one particular wavelength (or a very narrow waveband) referred to as, monochromatic light. Thus, to obtain an optical spectrum, the DS method includes selecting the particular wavelength (or very narrow waveband) from a wavelength range, facilitating the sample and reference interactions with light, detecting the resulting light, and repeating the process for each particular wavelength in the wavelength range.
According to the FT method, however, the sample light beam and the reference light beam contain light having a plurality of wavelengths (e.g., polychromatic light). To obtain an optical spectrum, the FT method includes modulating the sample light beam and the reference light beam, facilitating the sample and reference interactions with light, detecting the resulting light, and applying Fourier Transform techniques to the detected light. The FT method, instrumentation, and operation thereof are described in further detail below.
In general, the DS method and the FT method can be applied to the entire light spectrum (e.g., electromagnetic spectrum). However, the FT method is generally preferable to the DS method for infrared and near infrared applications because it produces substantially enhanced signal to noise ratios with respect to DS methodology. Additionally, since the FT method obtains the optical spectrum from exposing the sample and reference to only one light beam, rather than a plurality of light beams, the optical spectrum is generally obtained in a substantially shorter time using the FT method rather than the DS method. Thus, the FT method is often more desirable than the DS method when spectra must be obtained quickly or when certain physical features of the sample must be enhanced.
Irrespective of whether optical spectra are obtained using the DS method or the FT method, sensitivity, precision, and accuracy of the spectrophotometric measurements are critical. The sensitivity of a spectrophotometric measurement directly relates to the ability to detect small differences between samples having similar absorption properties. The greater the sensitivity, the smaller the difference that can be detected. The precision of a spectrophotometric measurement may be considered as a function of the ability to repeat the same measurement for an identical sample at different times. The accuracy of a spectrophotometric measurement may be considered as a function of the ability to correctly determine the numerical measure of the sample composition. The latter is critical, for example, when attempting to quantify an unknown element in a sample. Over a given range of concentration, the quantification is characterized by certain levels of precision and accuracy. However, below some critical lower limit of the concentration range, both precision and accuracy are adversely affected. This lower limit is the detection limit of the particular spectrophotometric instrument. As sensitivity increases, the detection limit decreases. Improvements in sensitivity, while retaining high levels of precision and accuracy are desirable.
For example, in FT methods, fluctuations in the light source power cause noise in the signal generated by the detector. The noise is ultimately carried through to the optical spectrum (e.g., transmittance spectrum). Additionally or alternatively, in FT methods, the various noises include digitization errors and tracking errors. In particular, digitization errors are a result of the finite resolution of the digitizer (i.e., electronics module, such as, analog to digital converter) limiting the ability of the digitizer to digitize signals generated by the detector with sufficient precision to indicate relatively small absorption peaks. This noise is introduced into the electronic signal at the stage of analog to digital conversion. Tracking errors are a result of the inconsistent sampling associated with the timing of the modulations introduced into the input light beam by an interferometer. The noise is ultimately carried through to the optical spectrum (e.g., transmittance spectrum). Such noise sources have traditionally not been considered in conventional devices that were incapable of providing the sensitivity required to make such sources apparent.